Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
coil patterns and core geometries, to reduce coil loss in HPMCs You will also contribute to teaching and supervising BSc and MSc student projects, and be co-supervisor for PhD students. Anyone who: has a
-
extraordinary access to computing resources, trans-disciplinary international researchers across many disciplines within catalysis, materials and computer sciences, robotics, power electronics, and other academic
-
. You will join the Junior Innovator program at Aarhus University, comprising young researchers from across all faculties. You will be encouraged to and supported in applying for external funding e.g
-
these nanocomposites, we are looking for a postdoc to further develop high performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core
-
of neuroimaging data and experience with computer programming, in particular Matlab. You have a strong interest in music. You have good interpersonal skills, are friendly, helpful, and able to contribute to a good
-
. Join us at the Department of Electrical and Computer Engineering, Aarhus University, where we are developing semantic-aware communication that leverage edge AI, semantic reasoning, and efficient time
-
Join us at the Department of Electrical and Computer Engineering at Aarhus University to help shape the future of sustainable water management. We’re looking for a motivated postdoc for a 1-year
-
backgrounds in: Civil, Architectural, and Environmental Engineering, Computer and Software Engineering, Computer Science, or a related discipline such as Mechanical Engineering. Candidates must have completed a
-
if the candidate is expected to have a keen interest in digital history, other team members will do the advanced computational analyses in collaboration with the rest of the team’s domain experts
-
contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with